To measure 3D shapes of dynamic scenes or objects, such as human facial expressions or body motions, speed, density and accuracy of measurement are crucial. Since passive stereo techniques have difficulties in reconstructing textureless surfaces densely and accurately, active 3D measurement techniques, especially those using high-speed structured light systems, have been extensively studied in recent years for capturing dynamic scenes.
Since a structured light system reconstructs 3D shape by projecting single or multiple patterns on a scene by a projector and capturing the scene by a camera, correspondences between feature points of projected pattern and captured scene is required. Many structured light systems temporally encode positional information of a projector's pixel into multiple patterns. Recently, structured light systems that can capture a dynamic scene by reducing the required number of patterns and increasing pattern speed have been proposed. These systems assume that there is little motion in a scene while a sufficient number of patterns for decoding are projected. In addition, the design of high-speed synchronization system is also an issue.
On the other hand, ‘one-shot’ structured light techniques using only single images in which positional information of the projectors' pixels are embedded into spatial patterns of the projected images have also been studied. Although the techniques can resolve the issues of rapid motions and synchronization, they typically use patterns of complex intensities or colors to encode positional information into local areas. Because of the complex patterns, they often require assumptions of smooth surface or reflectance, and the image processing tends to be difficult and to be low resolution. If the assumptions do not hold, the decoding process of the patterns may be easily affected and leads to unstable reconstruction.
As for a commonly used constraint to determine correspondences for structured light system, there is epipolar constraint. However, in case of a number of feature point is large or there are several feature points on a epipolar line because of a condition of arrangement of feature points, correspondences cannot be uniquely determined.
Shape reconstruction techniques with a structured light system, which encode positional information of a projector into temporal or spatial changes in a projected pattern, have been largely investigated. A technique using only temporal changes is easy to implement, so it has commonly been used thus far [Non Patent Literature 1].
Techniques using only spatial encoding of a pattern allow scanning with only a single-frame image (a.k.a. one-shot scan) [Non Patent Literature 2-4].
Non patent literature 5 shows reduced number of patterns by using both of temporal change and spatial change.
Although it does not strictly involve a structured light system, methods of shape reconstruction to include movement by spatiotemporal stereo matching are proposed [Non Patent Literature 6 and 7].
On the other hand, a technique allowing dense shape reconstruction based on a single image using a simple pattern, i.e. a set of stripes is proposed [Non Patent Literature 8].
[Non Patent Literature 1] S. Inokuchi, K. Sato, and F. Matsuda. Range imaging system for 3-D object recognition. In ICPR, pages 806-808, 1984.2
[Non Patent Literature 2] C. Je, S. W. Lee, And R.-H. Park. High-Contrast Color-stripe pattern for rapid structured-light range imaging. In ECCV, volume1, pages 95-107, 2004. 2, 5.
[Non Patent Literature 3] J. Pan, P. S. Huang, and F.-P. Chiang. Color-coded binary fringe projection technique for 3-d shape measurement. Optical Engineering, 44 (2): 23606-23615, 2005.
[Non Patent Literature 4] J. Salvi, J. Batlle, and E. M. Mouaddib. A robust-coded pattern projection for dynamic 3d scene measurement. Pattern Recognition, 19(11): 1055-1065, 1998.
[Non Patent Literature 5] S. Rusinkeiwicz: “Real-time 3D model acquisition”, ACM SIGGRAPH, pp. 438-446 (2002).
[Non Patent Literature 6] O. Hall-Holt and S. Rusinkiewicz. Stripe boundary codes for real-time structured-light range scanning of moving objects. In ICCV, volume 2, pages 359-366, 2001.
[Non Patent Literature 7] L. Zhang, N. Snavely, B. Curless, and S. M. Seitz. Spacetime faces: High-resolution capture for modeling and animation. In ACM Annual Conference on Computer Graphics, pages 548-558, August 2004. 2
[Non Patent Literature 8] T. P. Koninckx and L. V. Gool. Real-time range acquisition by adaptive structured light. IEEE Trans. on PAMI, 28(3):432-445, March 2006.